Hybrid Na(i)ve Bayes K-Nearest Neighbor Method Implementation on Speech Emotion Recognition

摘要：

　　Speech Emotion Recognition technique is incredible in that it can open a way of communication between human and computer.The applications vary from educational software,psychiatric diagnosis,and interrogation to intelligent toys.It has been a long way for researchers who dedicated to search for the best models for speech emotion recognition.This paper proposes a novel hybrid model that combines the K-Nearest Neighbor (KNN) model and the Na(l)ve Bayes (NB) classifier: a model which was inspired from the hybrid model of Support Vector Machine (SVM) and K-Nearest Neighbor method.The implementation of NB-KNN overcomes risks of SVM-KNN model and outperforms the original models that it is composed of.

关键词： Na(i)ve Bayes K-Nearest Neighbors Speech emotion recognition

作者: Seho Lee

作者单位: Department of International Studies Hankuk Academy of Foreign Studies Yongin, Republic of Korea

会议类型: 国际会议

会议名称: 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference(IAEAC 2015)(2015 IEEE先进信息技术,电子与自动化控制国际会议)

会议地点: 重庆

会议语种:英文

页码: 349-353

在线出版日期: 2015-12-19（万方平台首次上网日期，不代表论文的发表时间）